SHF: Small: Heterogeneous Memory Architectures for Future Many-core Systems

随着计算设备变得越来越普遍，它们正在从各种领域运行软件，从移动和图形空间一直到高性能、大数据服务器域。该软件必须实现高性能，同时出于环境原因消耗最小的功率。因此，计算系统正变得越来越异构化，在单个平台上容纳有利于不同软件域的不同硬件结构。虽然计算系统中的处理器传统上一直是这种异构性激增的焦点，但存储系统继续使用传统方法进行架构。因此，前瞻性的异构性计算系统的一个主要挑战是如何最好地设计存储系统来支持这种异构性。这些设计对于确保计算系统继续适应其不同的软件、性能和能量需求至关重要。这项研究为使用各种架构和技术构建存储系统提供了基础，以便以高性能且节能的方式运行来自不同域的软件。这项工作的重点是(1)构建一个系统的设计方法、软件特征和分析模型，以指导如何将不同的当前和未来的存储技术结合在一起，以最好地支持不同的计算系统软件，以及(2)设计一系列详细而灵活的实验平台来测试这些研究。该项目在许多方面对社会产生了影响，最突出的是：(1)在不牺牲高性能的情况下，降低当前和未来各种计算系统的能源消耗；(2)提供系统和严格的科学手段，使不同的内存技术和组件与不同的软件需求相匹配；(3)创建必要的评估工具，以适应未来的大量内存子系统研究。

As computation devices are becoming increasingly ubiquitous, they are running software from a variety of domains ranging from the mobile and graphics space all the way to high-performance, large-data server domains. This software must achieve high performance, while consuming minimal power for environmental reasons. As a result, computing systems are becoming increasingly heterogeneous, accommodating diverse hardware structures conducive to different software domains on a single platform. While processors in computing systems have traditionally been the focal point for this proliferation of heterogeneity, memory systems continue to be architected using traditional means. As such, a major challenge in forward-looking heterogeneous computing systems is how best to design memory systems to support this heterogeneity. These designs are crucial to ensure that computing systems continue to adapt to their varied software, performance, and energy requirements.This research provides the foundation to construct memory systems using a variety of architectures and technologies to run software from a variety of domains in a high-performance, yet energy-efficient manner. This work focuses on (1) constructing a systematic design methodology, software characterizations, and analytical models that guide how diverse current and future memory technologies should be combined to best support heterogeneous computing systems software, and (2) designing a range of detailed, yet flexible experimental platforms to test such studies. This project impacts society in a number of ways, most keenly by (1) reducing the energy consumption of current and future heterogeneous computing systems without sacrificing their high performance; (2) providing a systematic and rigorous scientific means to match different memory technologies and components to different software requirements; and (3) creating the evaluation tools necessary to accommodate a host of future memory subsystem research.